Xia Li, Ben-Kai Wei, Fan Li, Huan-Huan Yan, Jun Shen
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引用次数: 0
Abstract
Objective: This study aims to develop and validate a predictive model for short-term post-treatment anxiety trajectories in patients with breast cancer, utilizing baseline patient characteristics and initial anxiety scores to inform precise clinical interventions.
Methods: Baseline characteristics were collected from 424 patients diagnosed with breast cancer who underwent surgical treatment at our hospital between January 1, 2021, and December 30, 2022. Anxiety levels were assessed using the Self-Rating Anxiety Scale (SAS) scores at admission and at 3-, 6-, 9-, and 12-months post-treatment. Distinct trajectories of SAS score changes were identified and categorized. Variables were screened, and multiple models were developed. The optimal model was identified through comparative analysis, and a nomogram was generated following model simplification.
Results: We found three distinct trends in the trajectory of anxiety, but we grouped them into two broad categories: gradual reduction of anxiety and persistent anxiety. LM Model was established by logistic regression, and Model 1 and Model 2 were established by Random Forest (RF) and eXtreme Gradient Boosting (Xgboost) screening variables. The ROC curve areas in the validation set were 0.822 (0.757-0.887), 0.757 (0.680-0.834) and 0.781 (0.710-0.851), respectively. Model comparison, using Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI), identified the Lm model as optimal, which underwent further simplification and value assignment. Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) analyses confirmed the superiority of model-based interventions over general interventions.
Conclusion: Distinct anxiety trajectories are observed in patients diagnosed with breast cancer during the first 12 months post-treatment. Predictive modeling based on baseline characteristics is feasible although though further research is warranted.
期刊介绍:
Psychology Research and Behavior Management is an international, peer-reviewed, open access journal focusing on the science of psychology and its application in behavior management to develop improved outcomes in the clinical, educational, sports and business arenas. Specific topics covered in the journal include: -Neuroscience, memory and decision making -Behavior modification and management -Clinical applications -Business and sports performance management -Social and developmental studies -Animal studies The journal welcomes submitted papers covering original research, clinical studies, surveys, reviews and evaluations, guidelines, expert opinion and commentary, case reports and extended reports.